Multi-Objective Evaluation UtilitiesThis repository contains two Python scripts used to post-process multi-objective optimization experiments:- quality_indicator.py computes Pareto-based quality indicators across multiple runs and generates comparison plots.- resource_usage.py aggregates runtime and resource metrics from experiment logs and produces trend visualizations and summaries.The project is deliberately anonymous: no personal identifiers are included.## Prerequisites- Python 3.10+ (tested with Python 3.11)- Dependencies listed in requirements.txt (install with pip install -r requirements.txt)## Expected Data LayoutBoth scripts assume experiment outputs exist in sibling folders to the project root. By default the experiments are named:- nsgaii-ccm-eval-102-surrogate-50- nsgaii-ccm-eval-102-surrogate-falseEach experiment should contain multiple runs structured as:<experiment>/  run1/    experiment.json    algo_perf_stats.json  run2/    experiment.json    algo_perf_stats.json  ...Adjust the experiment names in the scripts if your folders differ.## Usage### Quality indicatorsquality_indicator.py merges Pareto fronts from all runs, computes metrics (HV, IGD+, GD+, epsilon) with pymoo and jMetalPy, and saves per-metric comparison plots.Run from the project root:zshpython quality_indicator.pyOutputs: PNG figures named like hv_quality_indicator_comparison.png in the current directory.### Resource usage analysisresource_usage.py loads algo_perf_stats.json files, normalizes differing JSON shapes, and computes mean/std trends for detected numeric resource columns. It also derives execution time and memory summaries when available.Run from the project root:zshpython resource_usage.pyOutputs are written under results/resource_trends/, including per-resource plots, an overview grid, optional CSV summaries, and markdown/ASCII tables for execution times.## Notes- The scripts rely on Matplotlib and Seaborn; a non-headless environment or appropriate backend may be needed for figure generation.- No external credentials or user-specific configuration are required; paths are relative to the repository root.